On 9/29/20 7:23 AM, h.park wrote:
> Dear experts,
>
> I was just wondering what the difference is between the
> robust.cluster and the robust.cluster.sem options for producing
> standard errors for a model that contains clustered data?
The distinction is similar to the (estimator) mlm vs mlr difference. The
former uses the classic formulas to compute 'robust' standard errors as
described in the SEM literature (robust.sem), while the latter uses the
'Huber-White' (or sandwich) formulas (robust.huber.white). Another way
of looking a this is that the default settings for specifying the
'bread' and the 'meat' of the sandwich formula is slightly different in
the two variants. But the results are often very similar (or indeed
identical).
This is (an old) document about it:
https://users.ugent.be/~yrosseel/lavaan/utrecht2010.pdf
The 'cluster' version simply extends these two variants to produce
cluster-robust standard errors.
Yves.